Author:
Toulni Hamza,Miyara Mounia,Filali Youssef,Koumétio Tékouabou Stéphane Cédric
Abstract
Urban mobility is one of the most important factors in the development of any nation and can act as a strong stimulant for economic expansion. Moreover, the rapid urban population growth in recent years has resulted in a substantial rise in the number of urban vehicles. But, the infrastructure on urban routes frequently isn’t adequate for a big number of urban vehicles. This inadequacy leads to several problems, including road insecurity, time loss and pollution. Congestion is one of the biggest issues and a significant hindrance to the road transportation system. In order to maximize the efficiency of the existing road network infrastructure, one idea is to leverage modern communication technologies to transmit traffic data, including the locations of accidents and risky road conditions. As a result, the congestion prevention system (CPS) presented in this study can assist drivers in improving their travel. CPS would be the best option for cutting down on travel time and fuel usage, avoiding traffic jams and lines, and ensuring that the current road infrastructure is used more effectively. The CPS is based on a methodology that examines accurate and valuable real-time traffic data. Experimental results for reducing urban traffic congestion have been highly encouraging according to the simulation of the system under various scenarios. We intend to include artificial intelligence in our system in future studies to improve it.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献